EP3600472B1 - Analysis and prediction of traumatic brain injury and concusion symptoms - Google Patents

Analysis and prediction of traumatic brain injury and concusion symptoms Download PDF

Info

Publication number
EP3600472B1
EP3600472B1 EP18771563.6A EP18771563A EP3600472B1 EP 3600472 B1 EP3600472 B1 EP 3600472B1 EP 18771563 A EP18771563 A EP 18771563A EP 3600472 B1 EP3600472 B1 EP 3600472B1
Authority
EP
European Patent Office
Prior art keywords
mir
hsa
mirnas
mirna
saliva
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
EP18771563.6A
Other languages
German (de)
English (en)
French (fr)
Other versions
EP3600472A4 (en
EP3600472A1 (en
Inventor
Steven D. HICKS
Frank A. MIDDLETON
Richard Uhlig
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Research Foundation of State University of New York
Penn State Research Foundation
Quadrant Biosciences Inc
Original Assignee
Research Foundation of State University of New York
Penn State Research Foundation
Quadrant Biosciences Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Research Foundation of State University of New York, Penn State Research Foundation, Quadrant Biosciences Inc filed Critical Research Foundation of State University of New York
Publication of EP3600472A1 publication Critical patent/EP3600472A1/en
Publication of EP3600472A4 publication Critical patent/EP3600472A4/en
Application granted granted Critical
Publication of EP3600472B1 publication Critical patent/EP3600472B1/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/40—Detecting, measuring or recording for evaluating the nervous system
    • A61B5/4058—Detecting, measuring or recording for evaluating the nervous system for evaluating the central nervous system
    • A61B5/4064—Evaluating the brain
    • C—CHEMISTRY; METALLURGY
    • C07—ORGANIC CHEMISTRY
    • C07K—PEPTIDES
    • C07K14/00—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof
    • C07K14/435—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof from animals; from humans
    • C07K14/705—Receptors; Cell surface antigens; Cell surface determinants
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B10/00—Other methods or instruments for diagnosis, e.g. instruments for taking a cell sample, for biopsy, for vaccination diagnosis; Sex determination; Ovulation-period determination; Throat striking implements
    • A61B10/0045—Devices for taking samples of body liquids
    • A61B10/0051—Devices for taking samples of body liquids for taking saliva or sputum samples
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/178—Oligonucleotides characterized by their use miRNA, siRNA or ncRNA

Definitions

  • the present invention relates to the field of detecting or diagnosing a concussion, mild traumatic brain injury (“mTBI”) or other traumatic brain injury (“TBI”) in adults and pediatric subjects.
  • the invention involves methods for correcting or normalizing values of six particular salivary micro RNA (miRNA) levels to compensate for temporal variations, such as circadian fluctuations, in salivary miRNA levels, as well as detecting abnormal temporal variations in said salivary mi-RNA levels that correlate with a concussion, mild traumatic brain injury (“mTBI”) or other traumatic brain injury (“TBI”).
  • miRNA salivary micro RNA
  • mTBI mild traumatic brain injuries
  • a mTBI is defined as a traumatic disruption of brain function that manifests as altered mental status, loss of consciousness ( ⁇ 20 minutes), or amnesia ( ⁇ 24 hours), with an initial Glasgow Coma Scale score of ⁇ 13 and lack of focal neurological deficits (J. Head Trauma Rehabil., 1993).
  • PCS post-concussion syndrome
  • S100 ⁇ is also produced outside the central nervous system (CNS) and is influenced by disease states including bone fractures and intra-abdominal injury (Kovesdi et al., 2010). These factors give it poor specificity as an mTBI diagnostic test (Bazarian et al., 2006). In addition, S100 ⁇ is influenced by exercise, limiting its utility in sports-concussions, a mechanism common in adolescents (Otto et al., 2000).
  • Micro ribonucleic acids are small, endogenous, non-coding molecules that influence protein translation throughout the human body (Nam et al., 2014). They are transported through the extracellular space by protective exosomes and micro-vesicles, or bound to proteins, which allows them to be easily detected in serum, CSF, or saliva (Bhomia et al., 2016; Valadi et al., 2007). Levels of tissue-specific mRNAs released by damaged cells might act as biomarkers of a human disease. Due to their abundance, stability at fluctuating pH levels, resistance to enzymatic degradation, and essential role in transcriptional regulation, miRNAs may be good biomarker candidates (Gilad et al., 2008).
  • miRNAs decreased (miR-765) and two miRNAs decreased (miR-16 and miR-92a) in eight subjects with sTBI; as well as two miRNAs (miR-92a and miR-16) increased in 11 subjects with mTBI compared to healthy volunteers (Redell et al., 2010).
  • Traumatic brain injury is an important public health problem, affecting at least 1.7 million individuals annually in the U.S. alone and is predicted to "surpass many diseases as the major cause of death and disability by the year 2020" according to the WHO.
  • the disorder is classified on a spectrum ranging from mild to severe, with mild TBI (mTBI) accounting for at least 85% of total TBI cases.
  • mTBI mild TBI
  • the incidence of mTBI is commonly regarded as under-reported, particularly in the context of sports competitions, where athletes often want to avoid being forced to stop participation and drop out of sporting competitions until completion of a formal medical evaluation and a return to play protocol.
  • mTBI has been referred to as a "silent epidemic”.
  • a typical head impact in mTBI induces rapid percussive (coup/contracoup) and/or torsional (rotational) damage to the brain, leading to parenchymal bruising and subarachnoid hemorrhage with direct brain cell loss, as well as stretching of axons, and diffuse axonal injury that may persist for years.
  • repetitive mTBI is associated with serious long-term sequelae including post-concussive syndrome and chronic traumatic encephalopathy (CTE), the latter often leading to cognitive impairment, neuropsychiatric symptoms, dementia, and pugilistic parkinsonism.
  • CTE chronic traumatic encephalopathy
  • mTBI often goes undiagnosed due to under-reporting, delayed onset of symptoms and the limited sensitivity of conventional assessment techniques in detecting mild brain injury, thereby hampering diagnostic, prognostic, and therapeutic approaches.
  • mTBI presents a diagnostic challenge, which has slowed efforts to examine the time course of its pathophysiology. Consequently, diagnostic, prognostic, and therapeutic approaches for mTBI are lacking. Compounding this issue, the failure to ascertain that mTBI has occurred in the first place can easily lead to repetitive mTBI and increase the risk of CTE. Thus, it is critically important to establish accurate and reliable diagnostic markers to aid in the early detection and diagnosis of mTBI, inform its prognosis, and ultimately provide a means to monitor response to treatment.
  • miRNAs are small non-coding RNAs ( ⁇ 22 nucleotides) that suppress target mRNA translation and stability for a large fraction of the transcriptome, and have emerged as useful biomarkers of several disorders including cancer and diabetes.
  • the influence of miRNAs on gene expression occurs both within the cells that synthesize them as well as within remote cells through extracellular trafficking. Once released from donor cells, miRNAs can travel through various extracellular fluids and exert regulatory effects on gene expression in recipient cells. Hence, miRNAs are important master regulators of cellular function within and between a wide range of cells and tissues.
  • dysregulation of specific miRNAs networks has been associated with several neurodegenerative disorders including Alzheimer's and Parkinson's disease, as well as alcoholism. While brain tissue is not readily available from living subjects with neurodegenerative disease, the fact that brain-specific miRNAs are released into peripheral biofluids suggests that miRNA profiles can serve as a proxy, or indirect readout of pathological processes occurring in the CNS.
  • identifying specific biomarkers for mTBI could facilitate early detection at the presymptomatic stage and will provide insight into novel targets to minimize or even prevent post-mTBI sequelae.
  • Support for the feasibility of using peripheral miRNA biomarkers to predict outcome measures following mTBI was recently provided in two studies on pediatric populations. The first study demonstrated considerable overlap in the miRNA present in both cerebrospinal fluid (CSF) and saliva (63%), and also indicated parallel changes for a number of these miRNAs in children with severe and mild TBI.
  • a follow up study from the same group showed that salivary miRNA patterns in children who were brought to a concussion clinic within a few days after mTBI could predict whether those children would develop acute concussive syndrome (ACS) or prolonged concussive syndrome (PCS) with high accuracy.
  • ACS acute concussive syndrome
  • PCS prolonged concussive syndrome
  • one of the elements missing from the aforementioned studies is any type of molecular or functional baseline assessment in the individuals that subsequently experienced a mTBI episode.
  • miRNAs are small non-coding RNAs that suppress protein expression that have emerged as useful biomarker candidates in cancer, diabetes, neurodevelopmental, and neurodegenerative disorders. Although miRNAs are made in all tissues and organs of the body, many of them show tissue-specificity. Moreover, miRNAs can act within the cells that synthesize them or be released into the extracellular space (EC) and travel in biofluids to affect other cells. Numerous studies have shown that miRNA expression profiles differ between healthy and diseased states and that the release of miRNAs into the EC appears elevated following tissue damage.
  • the inventors establish relationships between peripheral measures of miRNA, such as their salivary levels, objective assessment of likely mTBI severity, and sensitive indices of balance and cognitive function. Though many studies have identified miRNA targets that are dysregulated in adult TBI, none have examined their utility in predicting PCS in children.
  • the inventors have also assessed the clinical accuracy of salivary miRNAs in predicting occurrence and severity of PCS relative to the Sport Concussion Assessment Tool (SCAT-3).
  • SCAT-3 Sport Concussion Assessment Tool
  • the inventors sought to find whether miRNAs physiologically related to brain injury and repair would be altered in children with PCS, relative to controls with typical concussion duration, and whether the predictive value of salivary miRNAs would exceed that of current clinical tools, such as the SCAT-3. As shown herein, they found that salivary miRNA profiles can predict duration of concussion symptoms.
  • salivary miRNA profiles of children and adolescents with mTBI 1) reflect CSF profiles in children and adolescents with TBI; 2) accurately identify the presence of mTBI; and 3) differ from adult miRNA biomarkers of mTBI. Disrupted miRNAs are functionally related to brain injury and repair.
  • the systems and methods described herein solve many of the problems with existing methodologies of detecting, diagnosing and monitoring TBIs including those resulting from sporting injuries.
  • Read data on miRNA levels such as that obtained by RNA sequencing procedures, may be further normalized, for example, by comparison to levels of one or more invariant RNAs. In some embodiments levels of miRNAs are further normalized based on ciracadian fluctuations in miRNA levels in saliva.
  • the ones that concern the six particular miRNAs corresponding to miR-29c-3p, miR-26b-5p, miR-30e-5p, miR-182-5p, miR-320c, and miR-221-3p are part of the invention.
  • the other ones are not according to the invention and are present for illustration purposes only.
  • Saliva is a slightly alkaline secretion of water, mucin, protein, salts, and often a starch-splitting enzyme (as ptyalin) that is secreted into the mouth by salivary glands, lubricates ingested food, and often begins the breakdown of starches.
  • salivary glands lubricates ingested food, and often begins the breakdown of starches.
  • Saliva is released by the submandibular gland, parotid gland, and/or sublingual glands and saliva release may be stimulated by the sympathetic and/or parasympathetic nervous system activity. Saliva released primarily by sympathetic or parasympathetic induction may be used to isolate microRNAs.
  • Saliva may be collected by expectoration, swabbing the mouth, passive drool, or by other methods known in the art. In some embodiments it may be withdrawn from a salivary gland. In some embodiments, a saliva sample may be further purified, for example, by centrifugation or filtration. For example, it may be filtered through a 0.22 micron or 0.45 micron membrane, and all membrane sizes in between, and the separated components used to recover microRNAs. In other embodiments, proteins or enzymes that degrade microRNA may be removed, inactivated or neutralized in a saliva sample.
  • Some representative, but not limiting saliva collection and miRNA purification procedures include purifying salivary RNA in accordance with, for example, the Oragene RNA purification protocol using TRI Reagent LS, a TriZol purification method, or similar method.
  • the Oragene purification protocol generally includes multiple parts. In the first part, a sample is shaken vigorously for 8 seconds or longer and the sample is incubated in the original vial at 50°C for one hour in a water bath or for two hours in an air incubator.
  • a 250-500 ⁇ L aliquot of saliva is transferred to a microcentrifuge tube, the microcentrifuge tube is incubated at 90°C for 15 minutes and cooled to room temperature, the microcentrifuge tube is incubated on ice for 10 minutes, the saliva sample is centrifuged at maximum speed (> 13,000xg) for 3 minutes, the clear supernatant is transferred into a fresh microcentrifuge tube and the precipitate is discarded, two volumes of cold 95% EtOH is added to the clear supernatant and mixed, the supernatant mixture is incubated at -20°C for 30 minutes, the microcentrifuge tube is centrifuged at maximum speed, the precipitate is collected while the supernatant is discarded, the precipitate is dissolved in 350 ⁇ L of buffer RLT, and 350 ⁇ L of 70% EtOH is added to the dissolved pellet mixture and mixed by vortexing.
  • the first two parts may be followed by the Qiagen RNeasy cleanup procedure.
  • the purification process may further include a second purification step of, for example, purifying the saliva sample using a RNeasy mini spin column by Qiagen.
  • the purification of a biological sample may include any suitable number of steps in any suitable order. Purification processes may also differ based on the type of a biological sample collected from the subject. The yield and quality of the purified biological sample may be assessed via a device such as an Agilent Bioanalyzer, for example, to determine if the yield and quality of RNA is above a predetermined threshold.
  • microRNA or miRNA is a small non-coding RNA molecule containing about 22 nucleotides, which is found in plants, animals and some viruses, that functions in RNA silencing and post-transcriptional regulation of gene expression ( see Ambros et al., 2004; Bartel et al., 2004).
  • MicroRNAs affect expression of the majority of human genes, including CLOCK, BMAL1, and other circadian genes. Notably, miRNAs are released by cells that make them and circulate throughout the body in all extracellular fluids where they interact with other tissues and cells. Recent evidence has shown that human miRNAs even interact with the population of bacterial cells that inhabit the lower gastrointestinal tract, termed the gut microbiome. Moreover, circadian changes in the gut microbiome have recently been established.
  • miRNAs Small non-coding RNAs
  • RNAs suppress protein expression and that have emerged as useful biomarkers in cancer, diabetes, neurodevelopmental, and neurodegenerative disorders.
  • miRNAs are made in all tissues and organs of the body, many of them show tissue-specificity.
  • miRNAs can act within the cells that synthesize them or be released into the extracellular space (EC) and travel in biofluids to affect other cells. Numerous studies have shown that miRNA expression profiles differ between healthy and diseased states, and that the release of miRNAs into the EC appears elevated following tissue damage.
  • Epigenetic data includes data about miRNAs. Among the objectives of the inventors were to establish the relationship between peripheral measures of miRNA, objective assessment of likely mTBI severity, and sensitive indices of balance and cognitive function.
  • miRNA standard nomenclature system uses the prefix “miR” followed by a dash and a number, the latter often indicating order of naming. For example, miR-120 was named and likely discovered prior to miR-241. A capitalized “miR-” refers to the mature form of the miRNA, while the uncapitalized “mir-” refers to the pre-miRNA and the pri-miRNA, and “MIR” refers to the gene that encodes them.
  • miRNAs are known and may be obtained by reference to MirBase, Hyper Text Transfer Protocol (HTTP)://WorldWideWeb.mirbase.org/blog/2018/03/mirbase-22-release/ (last accessed March 19, 2018) and/or to Hyper Text Transfer Protocol (HTTP)://WorldWideWeb.mirbase.org/index.shtml (last accessed March 19, 2018).
  • HTTP Hyper Text Transfer Protocol
  • HTML Hyper Text Transfer Protocol
  • miRNA elements Extracellular transport of miRNA via exosomes and other microvesicles and lipophilic carriers is an established epigenetic mechanism for cells to alter gene expression in nearby and distant cells.
  • the microvesicles and carriers are extruded into the extracellular space, where they can dock and enter cells, and block the translation of mRNA into proteins (Hu et al., 2012).
  • the microvesicles and carriers are present in various bodily fluids, such as blood and saliva (Gallo et al., 2012), enabling us to measure epigenetic material that may have originated from the central nervous system (CNS) simply by collecting saliva.
  • CNS central nervous system
  • the inventors believe that many of the detected miRNAs in saliva are secreted into the oral cavity via sensory nerve afferent terminals and motor nerve efferent terminals that innervate the tongue and salivary glands and thereby provide a relatively direct window to assay miRNAs which might be dysregulated in the CNS of individuals.
  • extracellular miRNA quantification in saliva provides an attractive and minimally-invasive technique for brain-related biomarker identification in children with a disease or disorder or injury.
  • this method minimizes many of the limitations associated with analysis of post-mortem brain tissue or peripheral leukocytes (relevance of expression changes, painful blood draws) employed previously.
  • miRNA isolation from biological samples such as saliva and their analysis may be performed by methods known in the art, including the methods described by Yoshizawa, et al., Salivary MicroRNAs and Oral Cancer Detection, Methods Mol. Biol., 2013; 936: 313-324 or by using commercially available kits, such as mir Vana TM miRNA Isolation Kit).
  • circadian regulatory genes such as CLOCK and BMAL1.
  • CLOCK and BMAL1 a regulatory gene that influences circadian expression.
  • BMAL1 a regulatory gene that influences circadian expression.
  • saliva miRNA and microbe content a previously unknown relationship between saliva miRNA and microbe content as well as temporal influences (i.e., temporal variations) on miRNAs (and/or microbes) themselves.
  • the systems and methods described herein to normalize epigenetic data (sequencing data or other data) that experience temporal variations may be used in any suitable application where temporal variations may affect the data.
  • kits suitable for determining whether a subject has a disease, disorder, or condition including 2 or more miRNA probes of a probe set.
  • Each miRNA probe may include a ribonucleotide sequence corresponding to a specific miRNA described herein.
  • the kit further may include a solid support attached to the 2 or more miRNA probes.
  • the kit may further include at least one of the following: (a) one randomly generated miRNA sequence adapted to be used as a negative control; (b) at least one oligonucleotide sequence derived from a housekeeping gene, used as a standardized control for total RNA degradation; or (c) at least one randomly-generated sequence used as a positive control.
  • a probe set may include miRNA probes having ribonucleotide sequences corresponding to DNA sequences from particular microbiomes described herein.
  • One objective of the inventors was to compare changes in salivary miRNA following childhood TBI and to investigate the utility of circulating concentrations of miRNA as accurate and physiologically relevant markers of pediatric concussion.
  • Another objective of the inventors was to establish the relationship between peripheral measures of miRNA, objective assessment of likely mTBI severity, and sensitive indices of balance and cognitive function.
  • Another objective of the inventors that is not part of the present invention was to determine the relationship between peripheral measures of miRNA in the blood and saliva with objective measures of balance and cognitive function in adult subjects exposed to recent mild head trauma; to examine if any of the identified miRNAs are involved in specific biological pathways relevant to brain function and injury response; and to quantify the strength of the relationship between the miRNAs and functional measures and determine their potential diagnostic utility.
  • One objective of the inventors that is not part of the present invention was to provide a method of comparing the epigenetic data for a subject with a suspected traumatic brain injury (TBI) to one or more healthy control-subjects or a compendium of healthy control subjects, wherein each healthy control-subject is known not to have sustained a TBI or symptoms of a TBI, comprising:
  • Another objective of the inventors that is not part of the present invention was to provide a method of comparing epigenetic data for a subject having a suspected traumatic brain injury (TBI) to one or more healthy control-subjects or a compendium of healthy control subjects, wherein each healthy control-subject is known not to have sustained a TBI or symptoms of a TBI, comprising:
  • Another objective that is not part of the present invention was to provide a method of comparing epigenetic data for a subject with a suspected traumatic brain injury (TBI) to one or more healthy control-subjects or a compendium of healthy control subjects, wherein each healthy control-subject is known not to have sustained a TBI or symptoms of a TBI, comprising:
  • the miRNAs are selected from a group consisting of hsa-let-7f-5p, hsa-let-7i, hsa-miR-10a-5p, hsa-miR-10b-5p, hsa-miR-23a-3p, hsa-mir-23b, hsa-mir-25, hsa-miR-25-3p, hsa-mir-26a-1, hsa-mir-26a-2, hsa-miR-26a-5p, hsa-mir-26b, hsa-miR-26b-5p, hsa-mir-28, hsa-miR-28-3p, hsa-miR-28-5p, hsa-miR-29c-3p, hsa-mir-30b, hsa-miR-30e-3p, hsa-miR-30
  • Another objective of the inventors that is not part of the present invention was to provide method of monitoring the progression of an injury, disorder or disease state in a subject, comprising:
  • the miRNAs subject to time-of-day normalization are selected from the group consisting of hsa-let-7f-5p, hsa-let-7i, hsa-miR-10a-5p, hsa-miR-10b-5p, hsa-miR-23a-3p, hsa-mir-23b, hsa-mir-25, hsa-miR-25-3p, hsa-mir-26a-1, hsa-mir-26a-2, hsa-miR-26a-5p, hsa-mir-26b, hsa-miR-26b-5p, hsa-mir-28, hsa-miR-28-3p, hsa-miR-28-5p, hsa-miR-29c-3p, hsa-mir-30b, hsa-miR-30e-3p,
  • the miRNAs subject to time-of-day normalization are selected from the group consisting of hsa-let-7f-5p, hsa-let-7i, hsa-miR-10a-5p, hsa-miR-10b-5p, hsa-miR-23a-3p, hsa-mir-23b, hsa-mir-25, hsa-miR-25-3p, hsa-mir-26a-1, hsa-mir-26a-2, hsa-miR-26a-5p, hsa-mir-26b, hsa-miR-26b-5p, hsa-mir-28, hsa-miR-28-3p, hsa-miR-28-5p, hsa-miR-29c-3p, hsa-mir-30b, hsa-miR-30e-3p,
  • Another objective of the inventors that is not part of the present invention was to provide a method of detecting a miRNA sequence or a plurality of miRNA sequences in a biological sample, comprising:
  • the biological sample is a first biological sample taken at a first time point and the cDNA is a first cDNA, and the method further comprises:
  • kits for determining whether a subject has a traumatic brain injury comprising: a probe set comprising 2 or more miRNA probes having ribonucleotide sequences corresponding to ribonucleotide sequences of miRNAs selected from the group consisting of: hsa-let-7f-5p, hsa-let-7i, hsa-miR-10a-5p, hsa-miR-10b-5p, hsa-miR-23a-3p, hsa-mir-23b, hsa-mir-25, hsa-miR-25-3p, hsa-mir-26a-1, hsa-mir-26a-2, hsa-miR-26a-5p, hsa-mir-26b, hsa-miR-26b-5p, hsa-mir-28, hsa-miR
  • the kit further comprises a solid support attached to said probe set.
  • the kit further comprises: at least one of (a) one randomly-generated ribonucleotide sequence used as a negative control; (b) at least one oligonucleotide sequence derived from a housekeeping gene, used as a standardized control for total RNA degradation; or (c) at least one randomly-generated ribonucleotide sequence used as a positive control.
  • Another objective of the inventors that is not part of the present invention was to provide a method for assessing a post-concussion syndrome (PCS) in a subject that has had mild traumatic brain injury (mTBI), comprising:
  • Another objective that is not part of the present invention was to provide a method of detecting an array of micro RNAs (miRNA) in a saliva sample of a subject, the method comprising:
  • kits for assessing a post-concussion syndrome (PCS) in a subject diagnosed with a mild traumatic brain injury (mTBI) that had a concussion comprising: an array of nucleic acid probes that correspond to sequences of miRNA selected from the group consisting miR-769, miR-769-3p, miR-769-5p, miR-320c-1, miR-320c-1-3p, miR-320c-1-5p, miR-4792, miR-4792-3p, miR-4792-5p, miR-140, miR-140-3p, miR-140-5p, miR-629, miR-629-3p, miR-629-5p, miR-192, miR-192-3p, miR-192-5p, miR-145, miR-145-3p, miR-145-5p, let-7a, let-7a-3p, let-7s-5p, miR-133a, miR-133a-3
  • Another objective of the inventors that is not part of the present invention was to provide a method of treating a subject having post-concussion syndrome, comprising providing to the subject at least one of migraine medication, tension headache medication, an antidepressant, cognitive therapy, psychotherapy, anxiety medication, and depression medication, wherein the subject was identified as having post-concussive syndrome by the methods of the present invention.
  • a subject has at least of one symptom selected from the group consisting of headache, dizziness, fatigue, irritability, anxiety, insomnia, loss of concentration, loss of memory, noise sensitivity, and light sensitivity.
  • Another objective of the inventors that is not part of the present invention was to provide a method for monitoring brain injury status or prognosis in a subject, comprising: detecting one or more micro-RNAs associated with brain injury in saliva of the subject and evaluating or prognosing brain injury status when said microRNA is present in an amount significantly below or above that of a control subject without a brain injury, and optionally treating the subjects having brain injury.
  • prognosing comprises detecting an abnormal level of one or more microRNAs associated with balance and/or cognition.
  • the subject is a neonate or the subject is at least 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 months, or 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24 or 25 years old.
  • Another objective that is not part of the present invention was to provide a method for detecting pediatric TBI comprising detecting a level of let-7f microRNA above that of a value from a child not having pediatric TBI.
  • TBI traumatic brain injury
  • the TBI is mild TBI.
  • the detecting detects 6 miRNAs corresponding to miR-29c-3p, miR-26b-5p, miR-30e-5p, miR-182-5p, miR-320c, and miR-221-3p, in saliva.
  • detecting comprises detecting one or more miRNAs in serum.
  • detecting comprises detecting an abnormal level of one or more miRNAs associated with one or more measurements of balance of cognition or symptoms measurements described by the ClearEdge TM assessment system (Hyper Text Transfer Protocol Secure (HTTPS)://WorldWideWeb.clearedgetest.com/, last accessed January 22, 2018) or other functional measurement of balance and/or cognition.
  • ClearEdge TM assessment system Hyper Text Transfer Protocol Secure (HTTPS)://WorldWideWeb.clearedgetest.com/, last accessed January 22, 2018
  • At least one miRNA above-listed targets at least one of pathway associated with proteoglycan synthesis, mucin-type O-glycan biosynthesis, glycosaminoglycan biosynthesis or keratin sulfate biosynthesis, FoxO signaling, endocytosis, arrhythmogenic right ventricular cardiomyopathy, ErbB signaling, GABAergic synapses, regulation of stem cell pluripotency, morphine addiction, viral carcinogenesis, cAMP signaling, prolactin signaling, glioma, regulation of actin cytoskeleton, biotin metabolism, and adherens junction (zonula adherens).
  • At least one miRNA above-listed is enriched in an ubiquitin-mediated proteolysis pathway, an axon guidance pathway, or a TGF-beta signally pathway.
  • the method detects a subject with TBI or mTBI with an accuracy of at least 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, or 95%.
  • the method comprises monitoring the levels of one or more miRNAs as an index of exacerbation or amelioration of TBI or mTBI.
  • the method comprises treating a subject for TBI or mTBI and monitoring the levels of one or more miRNAs as an index of exacerbation or amelioration of TBI or mTBI before, during or after treatment.
  • compositions comprising probes and/or primers that identify at least one miRNA associated with TBI or mTBI in saliva or serum.
  • the probes and/or primers identify at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 50 or more miRNAs.
  • the composition comprises probes and/or primers that detect at least one miRNA that is enriched in an ubiquitin-mediated proteolysis pathway, an axon guidance pathway, or a TGF-beta signally pathway in a subject having TBI or mTBI.
  • the composition is a microarray, biochip or chip.
  • Another objective of the inventors that is not part of the invention was to provide a system for detecting miRNA in saliva comprising a microarray comprising probes or primers that collectively recognize multiple miRNA associated with TBI or mTBI, and optionally signal transmission, information processing, and data display or output elements.
  • system further comprises at least one element for receiving, and optionally purifying or isolating miRNA.
  • Another objective of the inventors that is not part of the invention was to provide a composition comprising one or more miRNAs that is/are deficient (lower than a healthy control) in a subject at risk of, or a subject having, TBI or mTBI in a form suitable for administration to an organelle, cellular compartment, tissue or site affected by TBI or mTBI; or a composition comprising one or more agents that lower or inactivate one or more miRNAs elevated, compared to a healthy control, in a subject at risk of, or a subject having, TBI or mTBI, in a form suitable for administration to organelle, cellular compartment, tissue or site affected by TBI or mTBI.
  • the composition is in a form of a natural or synthetic liposome, microvesicle, protein complex, lipoprotein complex, exosome or multivesicular body; or probiotic or prebiotic product.
  • One objective of the inventors that is not part of the invention was to provide a method for treating a subject at risk of TBI, or having TBI, comprising administering the composition disclosed herein 44 to a subject in need thereof.
  • the subject is a human.
  • the invention is practiced using a saliva sample.
  • expression levels of miRNAs can be determined by RNA sequencing, qPCR, sequencing miRNA array or a multiplex RNA profiling.
  • microRNA microRNA
  • the inventors have hypothesized that a portion of the miRNAs that target circadian genes would show strong circadian rhythms themselves. Because miRNAs can circulate throughout the body in all extracellular fluids, we measured them in human saliva. An additional reason to use saliva samples was to enable analysis of the relationship of miRNAs to the levels and diversity of microbes present in the human mouth, termed the microbiome.
  • Previous research in the lower GI tract has shown a strong relationship between host miRNAs and the resident bacteria.
  • circadian changes in the gut microbiome have been established. Consequently, one objective of the inventors was to obtain evidence for correlated changes in a subset of circadian oscillating miRNAs and microbes. See WO2018175422 .
  • the systems and methods described herein to normalize epigenetic data (sequencing data or other data) that experience temporal variations may be used in any suitable application where temporal variations may affect the data.
  • the systems and methods describes herein may be used in applications to detect the onset of medical conditions and/or changes in medical conditions - more specifically, to detect onset and/or changes in neurological disorders such as autism, sleep disorders and traumatic brain injury (TBI).
  • TBI traumatic brain injury
  • an objective of the inventors that is not part of the invention was to provide a method of normalizing epigenetic sequence data to account for temporal variations in microRNA (miRNA) expression, comprising:
  • Another objective of the inventors that is not part of the invention was to provide a method of monitoring progression of a disorder, disease state or injury in a subject, comprising:
  • miRNAs subject to time-of-day normalization are selected from the group consisting of Group A circaMiRs and/or those miRNA which share the seed sequences of the Group A circaMiRs.
  • miRNAs subject to time-of-day normalization are selected from the group consisting of Group A circaMiRs and Group B circaMiRs and/or those miRNA which share the seed sequences of the Group A circaMiRs and Group B circaMiRs.
  • the subject is a subject having a post-concussion syndrome (PCS). In another embodiment that is not part of the invention, the subject is a subject having TBI or mTBI.
  • PCS post-concussion syndrome
  • Another objective of the inventors that is not part of the invention was to provide a method of detecting a miRNA or a plurality of miRNAs in a first biological sample, comprising:
  • Another objective that is not part of the invention was to provide a method of detecting a miRNA or a plurality of miRNAs in a second biological sample, comprising:
  • the subject could be a subject having TBI, mTBI or a post-concussion syndrome (PCS).
  • PCS post-concussion syndrome
  • Another objective of the inventors that is not part of the invention was to provide a method for detecting an alteration in a temporal rhythm comprising:
  • the abnormal or altered pattern in an amount of one or more miRNAs is detected in one embodiment.
  • TBI Trigger football, soccer, rugby ice hockey, lacrosse, basketball, and other contact sports, tennis, golf, baseball, cricket, field and track, gymnastics, boxing, judo, karate, tae kwan do and other martial arts, equine sports, rodeo sports, diving including high diving and skin diving, skydiving, climbing, cycling, cheerleading, vehicular sports, and other sports; as well as vehicular accidents, and work-related impacts, falls and injuries.
  • sports-related falls and injuries such as those resulting from high-speed collisions in football, flag football, soccer, rugby ice hockey, lacrosse, basketball, and other contact sports, tennis, golf, baseball, cricket, field and track, gymnastics, boxing, judo, karate, tae kwan do and other martial arts, equine sports, rodeo sports, diving including high diving and skin diving, skydiving, climbing, cycling, cheerleading, vehicular sports, and other sports; as well as vehicular accidents, and work-related impacts, falls and injuries
  • miRNA expression levels are normalized to an expression level, or average expression level, of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or more housekeeping genes whose RNA expression level is substantially invariant; and/or wherein said miRNA levels are normalized to compensate for diurnal or circadian fluctuations in the expression of the one or more miRNA levels, normalized to compensate for fluctuations in the expression of the one or more miRNA levels due to food intake, or exercise that raises the heart rate; or adjusted to compensate for differences in age, sex or genetic background.
  • Housekeeping genes include those useful for calibration of RNA sequencing data such as those described by Eisenberg, et al., Trends in Genetics 29(10: 569-574, Cell Press (2013 ).
  • RNA sequencing RNA sequencing
  • qPCR qPCR
  • miRNA array miRNA array
  • multiplex miRNA profiling RNA sequencing
  • RNA sequencing RNA-seq
  • sequencing data raw read counts are quantile-normalized, mean-centered, and divided by the standard deviation of each variable; data are normalized to account for inter-sample count variations; and/or wherein data are normalized to expression of one or more invariant miRNAs to describe relative and/or absolute expression levels; and optionally further statistically analyzing the normalized data.
  • AUC Area under the curve
  • CNS Central nervous system
  • CSF cerebrospinal fluid
  • ELD extra-ventricular drain
  • GCS Glasgow coma score
  • miRNA micro-ribonucleic acid
  • mTBI mild traumatic brain injury
  • ROC receiver operating characteristic
  • sTBI severe traumatic brain injury
  • salivary miRNA is an easily measured, physiologically relevant, and accurate biomarker for identifying pediatric TBI.
  • miRNAs detected in CSF There were 214 miRNAs detected in CSF and 135 (63%) were also present in saliva.
  • Six miRNAs had parallel changes in both CSF and saliva miR-182-5p, miR-221-3p, mir-26b-5p, miR-320c, miR-29c-3p, miR-30e-5p). These six miRNAs demonstrated an area under the curve of 0.852 for identifying mild TBI status in pediatric subjects.
  • CSF samples previously collected for a study of F 2 -isoprostane levels in children and adolescents with sTBI were utilized for a longitudinal characterization of CSF miRNA. Briefly, ventricular CSF samples collected from 8 children with sTBI were selected at random for the current study. To remove sample selection bias, researchers were blind to participant characteristics prior to sample selection. The selected cohort included children ages 4-17 years with a Glasgow coma score (GCS) ⁇ 8 with a clinically-indicated extra-ventricular drain (EVD) for increased intracranial pressure following sTBI. Mechanisms of injury included fall and motor vehicle collision.
  • GCS Glasgow coma score
  • ESD extra-ventricular drain
  • CSF was passively extracted from each subject's EVD in a sterile fashion at three times following injury: day 1, day 4-7, and day 8-17. Age, sex, mechanism of injury, and times of collection were recorded for each subject (Table 1). Control CSF included 12 samples from three subjects (ages 1-8 years) undergoing clinically indicated spinal tap for epilepsy, or as part of a rule-out-sepsis protocol.
  • Table 1 Subject characteristics for sTBI and CSF controls Subject Age (years) Gender Mechanism of injury Day and time of collection 1 Day and time of collection 2 Day and time of collection 3 sTBI-1 4 F bike vs car Day 1, 0800 (6 hrs after EVD, 12 hrs after injury) Day 5, 0900 Day 10, 1000 sTBI-2 16 M MVA Day 1, 1500 (1 hr after EVD, 21 hrs after injury) Day 5, 0900 Day 10, 1000 sTBI-3 9 M MVA Day 1, 0800 (6 hr after EVD, 9 hrs after injury) Day 5, 1000 Day 10, 1100 sTBI-4 14 F ped vs car Day 1, 2300 Day 5, 2000 Day 8, 0930 sTBI-5 17 F MVA vs tree Day 1, 2000 (2 hrs after EVD, 17 hrs after injury) Day 4, 1500 Day 9, 1100 sTBI-6 17 M MVA vs tree Day 1, 1400 Day 5, 1045 Day 9, 0920 sTBI-7 8 F hit by fallen tree branch Day 1, 0945 Day 6, 0915
  • Salivary miRNA profiles obtained as part of the current study were investigated in subjects (age 5-21 years) with or without a clinical diagnosis of mTBI.
  • Exclusion criteria for the mTBI group included GCS ⁇ 12, clinical diagnosis of severe TBI, penetrating head injury, skull fracture, intracranial bleed, or symptoms attributable to underlying psychologic disorder (e.g. depression or anxiety).
  • the control cohort included 19 children and adolescents presenting to a Pediatrics Clinic for a regularly scheduled well child visit. Exclusion criteria for this group included a history of previous concussion, ongoing rheumatologic condition, or recent orthopedic injury. Subjects with periodontal disease, upper respiratory infection, seizure disorder, intellectual disability, history of migraine headaches, or drug/alcohol use disorder were excluded from both groups. Saliva samples were collected from each participant at the time of enrollment in a non-fasting state following an oral tap-water rinse through expectoration into an Oragene RE-100 saliva collection kit (DNA Genotek; Ottawa, Canada). Samples were shaken by hand 5-10 times and stored at room temperature for up to ten days prior to transfer into a 4°C refrigerator.
  • mTBI mild traumatic brain injury
  • SSRI selective serotonin re-uptake inhibitor
  • Med medicine
  • NSAID non-steroidal anti-inflammatory
  • LOC loss of consciousness
  • SCAT-3 sport concussion assessment tool-3
  • RNA samples were sequenced at the SUNY Molecular Analysis Core at Upstate Medical University using an Illumina TruSeq Small RNA Sample Prep protocol (Illumina; San Diego, California), an Illumina MiSeq instrument, and a targeted depth of three million reads per sample. Reads were aligned to the hg38 build of the human genome in Partek Flow (Partek; St. Louis, Missouri) using the SHRiMP2 aligner. Total miRNA counts within each sample were quantified with miRBase mature-microRNA v21. Saliva samples with less than 5 ⁇ 10 3 total counts were excluded from the final analysis, resulting in 60 mTBI and 18 control saliva samples.
  • fluorescence methods may be used to determine miRNA and/or microbiome levels.
  • ligands may be anchored in groups on a substrate.
  • the target miRNA and microbiome sequences may be tagged with a fluorescent tag (or non-fluorescent dye) either before or after it binds to the ligand.
  • relative intensity at each ligand group may be a measure of quantity of miRNA and/or microbiome present.
  • This method may be implemented on a chip-type assay.
  • chip-type-assays may be used to determine miRNA and/or microbiome levels.
  • isothermal amplification may be used to detect miRNA levels.
  • Fig. 5 shows quality analysis of cerebrospinal fluid RNA.
  • Examination of extracted RNA using an Agilent Bioanalyzer RNA Nanochip demonstrated relatively low RNA yields in cerebrospinal fluid samples, but consistent peaks at 18-25 nucleotides (consistent with successful miRNA extraction).
  • the miRNAs with the greatest physiologic relevance as concussion biomarkers were identified using a three-step procedure: 1) The miRNAs present only in sTBI CSF samples, or miRNAs with "altered” concentrations in sTBI CSF (measured as reads per million; RPM) were identified with a non-parametric Wilcoxon rank sum test with Benjamini Hochberg false detection rate (FDR) correction; 2) Concentrations (RPM) of these miRNA targets were investigated in mTBI saliva samples (compared to control saliva) using a Wilcoxon rank sum test; 3) The miRNAs "altered” in both CSF and saliva TBI samples were examined for parallel up- or down-regulation relative to controls ( Fig. 1 ).
  • the miRNAs of interest were inspected for longitudinal trends in both CSF and saliva concussion samples using a Spearman's rank correlation metric (correlating miRNA concentrations with days since injury). The diagnostic accuracy of these biomarker prospects was assessed with a multivariate logistic regression analysis and results were visualized with a receiver operating characteristic (ROC) curve.
  • ROC receiver operating characteristic
  • a secondary approach was employed involving a 100-fold Monte-Carlo Cross Validation (MCCV) technique alongside a 1/4 sample hold-out procedure in Metaboanalyst software (Xia et al., 2016). Relationships between medical/demographic characteristics and salivary miRNAs of interest were examined with Spearman's rank correlations. Analysis of medical and demographic data across mTBI and control groups was accomplished with a two-tailed student's t-test.
  • the miRNA biomarkers of mTBI underwent functional annotation analysis in DIANA mirPath v3 online software (Hypertext Transfer Protocol (HTTP)://snf-515788.vm.okeanos.grnet.gr/) using the microT-CDS algorithm to identify species-specific mRNA targets (Vlachos et al., 2015) DIANA ® mirPath identified gene ontology (GO) categories with significant (FDR ⁇ 0.05) target enrichment using a Fisher's Exact Test.
  • DIANA mirPath v3 online software Hypertext Transfer Protocol (HTTP)://snf-515788.vm.okeanos.grnet.gr/) using the microT-CDS algorithm to identify species-specific mRNA targets (Vlachos et al., 2015) DIANA ® mirPath identified gene ontology (GO) categories with significant (FDR ⁇ 0.05) target enrichment using a Fisher's Exact Test.
  • microT-CDS score ⁇ 0.99 A list of high confidence mRNA targets (microT-CDS score ⁇ 0.99) was interrogated for protein-protein interaction networks using moderate stringency settings (interaction score > 0.40) in String v10 software (Hypertext Transfer Protocol (HTTP)://string-db.org) (Szklarczyk et al., 2015).
  • HTTP Hypertext Transfer Protocol
  • epigenetic data e.g., epigenetic sequencing data
  • the epigenetic data may be normalized based on a time of day before analysis is performed to determine if a subject has experienced a traumatic brain injury, detect the severity or prognosis of the injury, or detect if a change in disease state due to traumatic brain injury has occurred.
  • miRNA quantities/levels may be normalized based on the time of day to account for naturally occurring changes in miRNA quantities/levels in a human/subject.
  • the time-of-day normalized miRNA quantities may be compared to a control/healthy reference subject or a compendium of control/healthy subjects to determine if the human/subject has traumatic brain injury or a change in their disease state. Further discussion of systems and methods for normalizing epigenetic data can be found in US2020157626 .
  • Salivary miRNA in miled TBI (mTBI). There were 214 salivary miRNAs with robust expression across both control and mTBI samples (Table 4). Forty of the miRNAs measured in saliva had nominal differences in normalized read counts and 10 had significant differences between control and mTBI groups. Nine of the miRNAs were down-regulated in mTBI saliva and 31 were up-regulated. Table 4.
  • miRNA differences in saliva mTBI samples miRNA p.value -log(p)10 FDR Fold Change log2(FC) hsa-miR-378d 4.57E-06 5.3402 0.00095645 8.8605 3.1474 hsa-miR-28-3p 8.94E-06 5.0487 0.00095645 1.9592 0.97027 hsa-miR-378f 4.40E-05 4.3569 0.0031362 6.2996 2.6553 hsa-miR-378g 0.00013739 3.862.
  • Predictive accuracy of miRNA biomarker panel When used in a random forest multivariate regression analysis differentiating mTBI and control saliva samples the six miRNAs had a combined area under the curve (AVC) of 0.852 ( Fig. 3A ). The algorithm misclassified 2/18 control subjects and 15/60 mTBI subjects ( Fig. 3B ), yielding a sensitivity of 75% and a specificity of 89% with 78% accuracy. A 100-fold cross validation procedure holding out 25% of samples at random validated this model with an AVC of 0.800 in the cross-validation set and an AVC of 0.917 in the hold-out set ( Fig. 3C ).
  • Table 8 Gene Ontology (GO) categories with targeted enrichment by the six miRNAs of interest GO Category p-value #genes #miRNAs ion binding 9.70E-19 256 6 organelle 1.14E-18 364 6 cellular protein modification process 4.42E-11 113 5 extracellular matrix disassembly 4.22E-10 18 5 collagen catabolic process 2.36E-09 16 4 nervous system development 2.68E-07 37 4 cellular nitrogen compound metabolic process 2.68E-07 171 6 extracellular matrix organization 3.81E-07 31 5 cellular_component 4.20E-07 592 6 molecular_function 2.04E-06 583 6 Fc-epsilon receptor signaling pathway 2.13E-06 15 4 neurotrophin TRK receptor signaling pathway 1.95E-05 18 4 catabolic process 7.89E-05 81 5 biosynthetic process 0.000339672 140 6 epidermal growth factor receptor signaling pathway 0.000477945 16 4 axon guidance 0.000769255 29 5 protein binding transcription factor activity 0.0017
  • the glymphatic system which helps regulate CSF turnover via peri-arterial tissue within the myelin sheath of cranial nerves and the olfactory bulb, represents a primary route by which brain-related molecules enter the peripheral circulation (Plog et al., 2015). Given the proximity of these structures to the oropharynx, it seems likely that the glymphatic system also plays a role in the transfer of brain-related miRNA to saliva.
  • miRNAs The role of miRNAs in the physiologic response to traumatic brain injury.
  • the six miRNAs identified in the current investigation are not merely correlated with the presence or absence of concussion. They also have neurobiological implications in the physiologic response to traumatic brain injury.
  • miR-320c is down-regulated in CSF of sTBI subjects and saliva of mTBI subjects. In both bio-fluids concentrations of miR-320c are directly correlated with time since injury (i.e. they return toward baseline over time).
  • MiR-320c is implicated in several pathways critical to nervous system function, including plasticity, mood, and circadian rhythm.
  • mRNA target of miR-320c is phospholipid phosphatase related 1 (LPPR1), a member of the plasticity-related gene family that is dynamically expressed during neuronal excitation and regulates neuronal plasticity Savaskan et al., 2004).
  • Plasticity-related genes are implicated in attentional deficits and in the current investigation concentrations of miR-320c were directly correlated with child report of increased daydreaming and parental report of child distraction. Longitudinal return of miR-320 levels toward baseline may mitigate these symptoms.
  • unfettered increases in miR-320c could lead to mood dysregulation commonly reported in post-concussive syndrome. This idea is supported by a study of miRNA expression in the adult forebrain following successful suicide completion that found significant increases in miR-320c (Lopez et al., 2014).
  • the salivary miRNAs identified in this investigation have potential application in the diagnosis and management of pediatric concussion.
  • This panel provides an objective measure of brain injury that is cheaper than MRI imaging approaches, more easily obtained than serum samples, and less time consuming than administering and scoring subjective concussion surveys.
  • miRNA signatures remain elevated nearly two weeks beyond injury and trend towards baseline during that time, they have clinical application at time of initial presentation to an acute clinic or emergency department setting, as well as at follow-up encounters with concussion specialists. Longitudinal trends in miRNA concentrations have potential utility for triaging specialist referrals, initiating personalized medical therapies, and tracking clinical responses to therapy.
  • the panel of miRNAs identified in this investigation misclassified only 17 out of 78 subjects.
  • the misclassified controls included one subject with food allergies and type 1 diabetes mellitus who was taking anti-depressant medication and a non-steroidal anti-inflammatory medicine, as well as one subject with no identifiable medical conditions.
  • Table 11 of miRNAs is a list of sixty eight (68) miRNAs that may be used in identifying and/or characterizing traumatic brain injury in a patient/subject. miRNAs that share the same seed sequences as any of the miRNAs in Table 1 may be used in identifying and/or characterizing traumatic brain injury in a patient/subject.
  • Table 11 TBI miRNA 1 hsa-let-7f-5p 2 hsa-let-7i 3 hsa-miR-10a-5p 4 hsa-miR-10b-5p 5 hsa-miR-23a-3p 6 hsa-mir-23b 7 hsa-mir-25 8 hsa-miR-25-3p 9 hsa-mir-26a-1 10 hsa-mir-26a-2 11 hsa-miR-26a-5p 12 hsa-mir-26b 13 hsa-miR-26b-5p 14 hsa-mir-28 15 hsa-miR-28-3p 16 hsa-miR-28-5p 17 hsa-miR-29c-3p 18 hsa-mir-30b 19 hsa-miR-30e-3p 20 hsa-miR-30e-5p 21 hsa-mir-92a-1 22 h
  • An objective of the inventors in this study was to determine the relationship between peripheral measures of miRNA in the blood and saliva with objective measures of balance and cognitive function in adult subjects exposed to recent mild head trauma; to examine if any of the identified miRNAs are involved in specific biological pathways relevant to brain function and injury response.; and to quantify the strength of the relationship between the miRNAs and functional measures and determine their potential diagnostic utility.
  • Blood collection was performed on-site by a trained phlebotomist into sterile BD Vacutainer SST tubes (Becton-Dickenson), allowed to sit for 20 minutes and centrifuged per manufacturer instructions. Saliva was collected by expectoration into Oragene RNA collection vials (RE-100, DNAGenotek, Ottawa, ON) or by swab absorption using the Oragene Nucleic Acid Stabilizing Kit swab (P-157, DNAGenotek, Ottawa, ON).
  • the MMA subjects included 40 males and 2 females, with an average age of 26.5 yrs and mean BMI of 24.6. Two-thirds (66%) of the subjects self-reported as Caucasian, 17% African American, and 14% Hispanic. A total of 29% of the fighters also reported a prior history of concussion, without complication. Serum samples from a subset of these fighters were used to evaluate potential changes in pre- and post-fight protein biomarkers of mTBI. These samples were derived from 24 fighters (23 male), aged 18 - 42 (mean 24.9 yrs), with a mean BMI of 23.4.
  • Luminex assay Using a custom 8-plex Magnetic Luminex ® Screening Panel (R&D Systems, Minneapolis, MN; catalog # LXSAHM), serum samples were assayed for the expression level of BDNF, CCL2/MCP-1, CRP, ICAM1, IL-6, NSE2, S100B, and VCAM according to the manufacturer's protocol. The sensitivity limits for each analyte were 0.32, 9.9, 116, 140, 87.9, 1.7, 4.34, and 238 pg/mL, respectively. Sample fluorescence was read on a Bio-Rad Bioplex ® 200 System and analyzed using Bioplex ® Manager 6.1 software (Bio-Rad, Hercules, CA).
  • ELISA Serum levels of UCHL1, MBP, GFAP were detected using Mybiosource ELISA kits (MyBiosource, Inc., San Diego, CA) according to the manufacturer's instructions. The catalog numbers and detection limits were as follows: UCHL1 (# MBS2512760), 78.125-5000pg/mL; MBP (#MBS261463), 1000 pg/ml-15.6 pg/ml; and GFAP (#MBS262801), 20 ng/ml-0.312 ng/ml. The optical density of the peroxidase product was measured spectrophotometrically using a Synergy 2 microplate reader (Biotek, Winooski, VT) at a wavelength of 450 nm.
  • RNA Isolation RNA was isolated from serum and saliva using the miRNeasy Serum/Plasma Kit (Qiagen Inc) according to the manufacturer's instructions. Serum: frozen serum samples were thawed on ice, and 200 ⁇ L of serum was added to ImL of QIAzol lysis reagent. Following vigorous vortexing, 200 ⁇ L of chloroform was added and the samples were incubated for 5 minutes at room temperature (RT), then centrifuged at 12,000 x g for 15 minutes at RT. The resultant aqueous phase was removed, mixed with 1.5 volumes of 100% ethanol, transferred to an RNeasy MinElute spin column, and centrifuged for 15 seconds.
  • RT room temperature
  • RNA was eluted with 30 ⁇ L of RNase-free water.
  • Saliva refrigerated saliva samples originally collected in an Oragene vial or swab collection kit were incubated at 50°C for 1 hour. A 250 ⁇ L aliquot was then removed, transferred to a microcentrifuge tube, incubated at 90°C for 15 minutes, and cooled to RT. 750 ⁇ L of QIAzol lysis reagent was added, and the sample was vortexed vigorously for 1 minute, and incubated for 5 minutes at RT.
  • RNA quality was assessed using the Agilent Technologies Bioanalyzer on the RNA Nanochip.
  • RNA Sequencing Stranded RNA-sequencing libraries were prepared using the TruSeq Stranded Small RNA Kit (Illumina) according to manufacturer instructions. Samples were indexed in batches of 48, with a targeted sequencing depth of 10 million reads per sample. Sequencing was performed using 36 bp single end reads on an Illumina NextSeq 500 instrument at the SUNY Molecular Analysis Core (SUNYMAC) at Upstate Medical University. FastQ files were trimmed to remove adapter sequences, and alignment performed to the mature miRbase21 database using the Shrimp2 algorithm in Partek Flow (Partek, Inc., St. Louis, MO).
  • PCA principal component analysis
  • HTH head
  • MCCV Monte-Carlo Cross-Validation
  • Time 1 thus contained samples from subjects who showed up to the MMA match but did not participate in a fight, and still provided a biofluid sample (these serve as controls for non-specific effects of the event) as well as subjects that participated in a match but experienced no hits to the head (these serve as exercise controls). Collectively, these are referred to as Time 1 Controls.
  • the remaining temporal bins were from fighters who participated in a match and received at least 2 hits to the head (HTH). These were grouped by collection time point into Time 1 HTH (within 1 hour post-fight), Time 2 HTH (2-3 days post-fight), and Time 3 HTH (7 days post-fight).
  • the temporal profiles of all miRNAs with significant Time effects were visualized and subjected to supervised classification analysis to identify the most salient patterns. miRNAs with expression profiles of interest were then subjected to functional analysis using Diana Tools miRpathv3 and compared with the miRNAs from the Subject Binning analysis.
  • MMA fighter balance and cognitive function was performed using a version of the ClearEdge TM assessment system developed by Quadrant Biosciences Inc. (Syracuse NY), that measured body sway in three dimensions during 8 different stances, as well as body sway and completion times during the performance of dual motor and cognitive tasks.
  • the dual tasks and cognitive tasks were completed by each subject using a hand-held tablet computer (Toshiba, Model: WTB-B) and stylus.
  • the analysis of body sway (balance) was measured via the use of an inertial sensor worn by each subject around the waist that sampled motion in all three planes at a frequency of 250 Hz with the resulting data downloaded from each tablet for post-processing.
  • Stances were held by each subject for 30 seconds, with their shoes removed, while standing either on the floor or on a foam pad and data were obtained with the eyes open or closed.
  • the feet were either positioned side by side with the ankles or medial aspects of the feet touching, or they were in a tandem position with the dominant foot forward and the non-dominant foot positioned directly behind and the heel of the lead foot in contact with the toes of the trailing foot.
  • the cognitive component of the dual tasks included a digital version of the Trails A and Trails B tasks, and an auditory working memory task (Backward Digit Span) in addition to a simple dual task of merely holding the tablet steady while maintaining fixation on it.
  • Trails A subjects had to quickly connect an ascending series of encircled numbers (1-2-3 etc.) with a stylus on the screen.
  • Trails B subjects had to connect an ascending series of encircled numbers and letters in an alternating alpha-numeric sequence (1-A-2-B-3-C etc.).
  • the Backward Digit Span task consisted of measuring reverse-order recall of increasingly long number sequences that were delivered to each subject via headphones. Altogether, 14 tasks were measured on the fighters. Notably, it was only possible to obtain simultaneous functional and biofluid measures on the same subjects in approximately half (48%) of the sample times.
  • the functional data were converted to standardized difference measures by comparison of all post-fight timepoints with a common pre-fight timepoint within each subject. Missing datapoints for some of the Backward Digit Span task measures were filled in using a K-nearest neighbor approach.
  • the functional data were screened for sphericity prior to statistical analysis using principal component analysis (PCA).
  • PCA principal component analysis
  • a two-way (Sample Type x TBI Classification) analysis of variance (ANOVA) was performed to screen for functional measures with a significant effect of the TBI classification assignment at the time of collection with the False Discovery Rate (FDR) ⁇ 0.05.
  • FDR False Discovery Rate
  • two-way ANOVA was performed in a manner similar to the miRNA measures to identify functional outcomes that were related to the likelihood of an HTH or the temporal interval since an HTH.
  • Table 14 Functional Outcome Measures Standing on floor 1) Sway during Two Legs Eyes Open (TLEO) 2) Sway during Two Legs Eyes Closed (TLEC) 3) Sway during Tandem Stance Eyes Open (TSEO) 4) Sway during Tandem Stance Eyes Closed (TSEC) Standing on foam pad 5) Sway during TLEO Foam Pad (TLEOFP) 6) Sway during TLEC Foam Pad (TLECFP) 7) Sway during TSEO Foam Pad (TSEOFP) 8) Sway during TSEC Foam Pad (TSECFP) Dual task 9) Sway during Holding Tablet (HT) 10) Sway during Dual Task Trails B Task (TMB_Dual_Bal) 11) Sway during Dual Task Digit Span Backwards (DSB_Bal) 12) Completion Time for Trails A Task (TMA_Cog) 13) Completion Time for Trails B Task (TMB_Cog) 14) Completion Time for Dual Task Digit Span Backwards (DSB_Cog
  • 7A-7D are whisker box plots of consistent changes in body sway post-fight versus pre-fight seen during two different functional tests in subjects who provided saliva or serum samples and were classified into three different TBI likelihood categories ( Low, Moderate, Very Likely ). Note that one of the sway measures was obtained during a cognitive task performance (Digit Span Backwards, upper) while the other was obtained during a balance test performed without visual guidance (Two Legs, Eyes Closed, lower). The increase in sway is evident for both sets of measures in the Moderate and Very Likely groups compared with Low TBI likelihood groups.
  • TBI likelihood Fig. 8 In addition to the two functional measures that showed clear stepwise gradients of impairment in the MMA fighters according to probability of TBI, there were two other significantly changed functional measures that did not show as clear a pattern according to TBI likelihood Fig. 8 . These included the sway during the Trailmaking B task (TMB_Bal) and the difference score of the completion time for the Trailmaking A task (TMA_Cog). For the TMB_Bal task, there was a suggestion of elevated scores in the Very Likely group, particularly in subjects providing a serum sample, but it was not as evident in the subjects who provided a saliva sample Fig. 8 (A-B, top).
  • Fig. 8 shows less consistent changes in body sway or completion time scores post-fight versus pre-fight seen in two different functional tests, in subjects grouped by TBI likelihood (same conventions as Figs. 7A-D ). Note slightly elevated scores in the Very Likely group of the TMB_Bal task (upper) when a serum (but not a saliva) sample was taken, and the slight elevation in the TMA_Cog score (lower) in the Moderate (but not Very Likely ) group.
  • Serum Protein Biomarkers The potential changes in levels of 11 serum proteins in 24 fighters immediately after their fight compared to pre-fight were examined. These proteins included UCHL1, MBP, GFAP (analyzed by ELISA) and BDNF, CCL2/MCP-1, CRP, ICAM1, IL-6, NSE2, S100B, and VCAM (analyzed by a custom Luminex assay. All of the IL-6 sample values were below the lowest standard concentration for that assay, and thus no results were available for this analyte. The majority (21/24) of the S100B values for pre-fight samples were also below the lowest standard concentration. However, 16 of the samples from the same fighters had measurable levels of S100B post-fight.
  • the pre-fight concentration were set equal to half the lowest post-fight concentration value (22.7 pg/mL).
  • 11A shows intermixing of the samples, with only a slight suggestion of separation of Very Likely serum samples (green/grayscale boxes) from the main data cloud. When all the data are collapsed, the change values are distributed in a highly normal fashion (11B)-lower).
  • a total of 21 miRNAs demonstrated significant changes according to the TBI likelihood classification as shown by Fig. 44 and Table 16. Of these, two also showed a significant effect of Fluid type and two showed an Interaction effect of Fluid type x TBI likelihood.
  • Fig.44 shows the effects of TBI likelihood on miRNA expression changes in serum and saliva post-fight compared to pre-fight. A total of 925 miRNAs were tested, with 21 showing a significant main effect of TBI likelihood, of which two also showed a significant main effect of fluid and two showed a significant Fluid x TBI interaction.
  • Table 16 miRNAs with changes related to TBI likelihood.
  • stepwise linear regression was used to preselect an optimal number of miRNAs for prediction of Hits to the Head (HTH) values, and this set of 13 was subjected to 100-fold Monte Carlo Cross Validation (MCCV) using Random Forest, in order to estimate classification accuracy for distinguishing Very Likely from Low likelihood TBI samples.
  • MCCV Monte Carlo Cross Validation
  • Fig. 13A-13F Examples of some of the 21 miRNAs in serum and saliva with changes in expression post-fight are shown in Fig. 13A-13F .
  • some of these miRNAs showed a pattern of increased expression in both biofluids after TBI ( Fig. 13A-13B , miR-30b-5p, top), while others showed a change that was most evident in only a single biofluid type.
  • miR-92a-3p Fig. 13C-D , middle
  • miR-122-5p Fig. 13E-13F , bottom
  • 13A-13F depicts whisker box plots illustrating changes in miRNA expression levels in saliva and serum following a TBI. Each row represents a different miRNA example (three miRNAs are shown), and each dot represents the expression level of that miRNA in a particular sample. Note that some miRNAs showed a pattern of increase in both biofluids after TBI (30b-5p, top), while others showed a change that was most evident in only a single biofluid type (e.g., 92a-3p and 122-5p).
  • More than half of the miRNAs (n 13) showed mixed directionality of changes in the two biofluids, with an increase or decrease in one biofluid accompanied by no change or a change in the opposite direction in the other biofluid.
  • 7 miRNAs did show changes in the same direction in the two biofluids, including 2 that increased (miR-10b-5p, miR-30b-5p) and 5 that decreased (miR-3678-3p, miR-455-5p, miR-5694, miR-6809-3p, and miR-92a-3p).
  • the top ten ranked KEGG pathways four were of particular interest for their potential relevance to TBI.
  • Fig. 14 shows enrichment of changed miRNAs for target genes in the KEGG Ubiquitin-mediated proteolysis pathway. In this pathway, 80 genes were targeted by a total of 19 miRNAs. Genes targeted by 1 miRNA are shown in yellow, and genes targeted more than 1 miRNA are shown in orange. Genes in green have miRNAs that are predicted to target them but none of these were contained in the list of 21 changed miRNAs. Genes in white do not have predicted miRNAs that target them.
  • Fig. 15 depicts enrichment of changed miRNAs for target genes in the KEGG TGF-beta signaling pathway (conventions same as Fig. 10 ). This pathway contained 46 genes that were predicted to be targeted by 20 miRNAs. Fig.
  • FIG. 16 shows enrichment of changed miRNAs for target genes in the KEGG Axon guidance pathway (conventions same as Fig. 10 ). This pathway contained 70 genes that were predicted to be targeted by 17 miRNAs.
  • Fig. 17 shows enrichment of changed miRNAs for target genes in the KEGG Glutamatergic synapse pathway (conventions same as Fig. 10 ). This pathway contained 61 genes that were predicted to be targeted by 20 miRNAs.
  • the first set of miRNAs showed an acute increase in saliva immediately post-fight that then returned to normal levels on days 2-3 and 1 week post-fight. This pattern was evident primarily in saliva samples and accurately described 12 of the 47 miRNAs with significant ANOVA effects ( Fig. 38A ). These were termed Acute Saliva Response (ASR) miRNAs. Remarkably, these same miRNAs demonstrated a distinctly different pattern of change in the serum samples. Specifically, none were increased, a small number showed no change, and several showed a delayed decrease, beginning at 2-3 days post-fight ( Fig. 38B ).
  • ASR Acute Saliva Response
  • the second pattern was a delayed effect, usually a graded increase or decrease in expression on days 2-3 that reached a peak at 1 week post-fight, and was not present at the initial post-fight time point.
  • This pattern was highly apparent in serum samples, and accurately described changes in 13 of the 47 miRNAs ( Fig. 39A ). These were termed Delayed Serum Response (DSR) miRNAs. Notably, these same miRNAs did not exhibit a similar pattern in the saliva samples. Rather, most were either unchanged or showed a trend for modestly increased expression at earlier time points, including potentially non-specific or exercise-related changes ( Fig. 39B ).
  • DSR Delayed Serum Response
  • the miRGator3.0 tool was used to ascertain the potential for the saliva and serum miRNAs to reflect release from central nervous system sources.
  • a miRNA was considered "brain enriched” if its median expression across multiple CNS sources exceeded the median expression in any of the 31 non-neural organs and 51 non-neural tissues in the miRGator 3.0 database.
  • the 11 ASR miRNAs with mapping information available four were identified as brain enriched, suggesting possible CNS origin for the salivary miRNAs that increased within an hour post-fight (Table 20). This finding stands in contrast with the DSR miRNAs, where of the 11 serum miRNAs with mapping information available, only 1 was found to be brain enriched (Table 20).
  • Figs. 38A-38B show 12 miRNAs were identified with acute temporal effects (all increases) at the 1 hr Post-fight time point (blue shaded area) in saliva samples (upper) that exceeded those at the non-specific exercise- or event-related timepoint (green shaded area). Note that most of the miRNAs returned to near baseline by 2-3 days Post-fight. The pattern for the same miRNAs was distinctly different in serum (several were unchanged and several had delayed decreases).
  • Figs. 39A-B depict miRNAs identified with predominantly delayed increases (solid lines) and decreases (dashed lines) in serum at 1 week Post-fight (upper, blue shaded area) that exceeded those at the non-specific exercise- or event-related timepoint (green shaded area). Note that these miRNAs were unchanged or showed some evidence for non-specific increases in saliva (lower).
  • the first pathway that was directly compared was the Glutamatergic synapse pathway Fig. 40 . It was noted that many of the same genes were targeted by miRNAs found in saliva or serum. Some exceptions to the overlapping targets included SLC1A2/EAAT2 (only targeted by acute response salivary miRNAs) and Glutaminase/GLS2 and the vesicular glutamate transporter/SLC17A7 (only targeted by the delayed response serum miRNAs).
  • FIG. 40A-B shows enrichment of changed miRNAs for target genes in the KEGG Glutamatergic synapse pathway (conventions same as Fig. 10 ). Note that both saliva miRNAs and serum miRNAs target many of the same genes in this pathway.
  • Figs. 41A-41B shows enrichment of temporally-regulated miRNAs in pathways involved in learning and memory from the saliva (Long-term depression, upper), and serum (Long-term potentiation, lower) (same conventions as Fig. 10 ).
  • Fig. 42 shows functional measures correlated with acute saliva response miRNAs.
  • Solid lines show cognitive measures (higher values indicate better performance).
  • Dashed lines show normalized body sway measures (higher values indicate worse performance).
  • cognitive measures showed a trend for drop in performance at the 1 hr post-fight time point, while body sway showed an increase atthe same time point.
  • two of the cognitive measures (TMB_COG and TMB_Dual_COG) showed an apparent learning effect (improved performance across time, other than the immediate post-fight time point).
  • TMB_COG two of the cognitive measures
  • TMB_Dual_COG showed an apparent learning effect (improved performance across time, other than the immediate post-fight time point).
  • a learning effect was also seen in 1 of the balance measures (TLEOFP), with decreased body sway evidence across time, other than the immediate post-fight time point.
  • Serum The serum miRNAs that were identified with temporal effects tended to show delayed changes, with increases and decreases seen at 2-3 days and 1 week post-fight. Thus, these were examined separately from the saliva miRNAs using PCA on the combined data from 31 total samples. This revealed strong reciprocal loadings for three miRNAs that showed delayed decreases in expression (miR-139-5p, miR-30c-1-3p, miR-421) and six miRNAs (miR-6809-3p, miR-5588-5p, miR-3678-3p, miR-4529-3p, miR3664-3p, and miR-4727-3p) and four functional measures (TSEO, DSB_Bal, TMB_DualBal) that showed delayed increases (Table 25; Fig.
  • Fig. 43 shows functional measures correlated with delayed serum response miRNAs.
  • Solid line shows a balance measure (TSEO) with apparent learning effects (decreased sway at the No HTH control and 1 hr Post-fight time points) that subsequently showed increased sway at 2-3 days Post-fight.
  • the dashed lines indicate two balance measures with delayed effects (TMB_Dual_Bal) or acute plus delayed effects (DSB_Bal).
  • the inventors investigated saliva and serum molecular measures and neurocognitive and balance measures in young adult athletes, both at baseline and various time points following an MMA event, with the goal of establishing diagnostic measures that might accurately predict the likelihood of mTBI or sports-related concussion or head impact. This was performed using four complementary approaches. First, the inventors binned subjects on mTBI probability based on the number of hits to the head that they received in an MMA bout and analyzed a set of potential serum protein biomarkers in a subset of the subjects, based on claims in the existing literature.
  • the inventors then examined serum and salivary miRNA data as well as neurocognitive and balance measures using two-way ANOVA and ROC curve analyses to identify other potential measures which could distinguish low-probability from high-probability concussion samples.
  • the inventors examined the miRNA data using repeated measures ANOVA and revealed molecular biomarkers with either acute or delayed temporal effects relative to the MMA bout. This was true of both saliva and serum miRNAs, although the patterns tended to differ in the two biofluids.
  • balance measures particularly those involving high dual-task cognitive demands, such as the TMB_Dual_Bal and DSB_Bal, may reveal their maximal effects at a somewhat delayed time point rather than acutely ( Fig. 43 ).
  • TSECFP task likely represents the most difficult task and subjects can only use proprioceptive cues but not visual information, and this did not demonstrate any apparent improvement across time.
  • Protein biomarkers Numerous studies in both human subjects and rodent models have examined the potential utility of different serum proteins in the context of mTBI and more commonly severe TBI. The inventors examined a set of 11 potential biomarkers in a subset of our MMA fighter samples, obtained immediately pre- and post-fight. While some of these proteins showed elevations post-fight relative to pre-fight, this was largely true regardless of whether subjects experienced many (or any) hits to the head. The only exception to this was UCHL1, which showed an increase post-fight that was correlated with the number of hits to the head.
  • miRNA biomarkers There have been several human studies published on potential blood or other biofluid measures of mTBI using miRNAs, including recent work on TBI in teenage children. These studies have generally focused on examination of a single time point in a cross-sectional comparison of mTBI and control subjects, or on focused examination of a small number of miRNAs across multiple time points. Very few studies have utilized exercise- or non-head injury (e.g., musculoskeletal injury controls in mTBI). Other studies in laboratory animals have generally involved rodents, and often employed multiple timepoints or open TBI procedures more analogous to severe TBI. Open procedures clearly introduce conditions that are beyond the scope of what occurs in mild TBI in normal circumstances. Our study attempted to explore the issues of mTBI severity and time on the miRNA data and place the changes within the context of the functional data and previous findings in the field.
  • the brain stem provides a potential CNS-to-oral cavity route via the sensory (V, VII, IX) and motor (XII, X, XII) cranial nerves that innervate the salivary glands and tongue.
  • the study included subjects of age 7 to 21 years with a clinical diagnosis of mTBI.
  • the mTBI group was composed of 61 children and adolescents who presented to the Penn State Hershey Medical Center for an evaluation of mTBI within 14 days of initial head injury. This 14 day cutoff period was chosen based on previous research indicating that most clinical symptoms and biomarker profiles return to baseline within two weeks of concussion (McCarthy et al., 2015).
  • Subjects with a GCS ⁇ 12 at the time of injury a clinical diagnosis of sTBI, penetrating head injury, skull fracture, intracranial bleeding, or those suffering from symptoms that could be attributed to depression or anxiety were excluded. Additional exclusion criteria were: primary language other than English, wards of the state, periodontal disease, upper respiratory infection, focal neurologic deficits, history of migraine, and drug/alcohol abuse.
  • Subjects and parents were contacted via telephone four weeks after the date of initial injury for re-evaluation of symptoms with the child SCAT-3. Thirty subjects with a SCAT-3 score ⁇ 5 on either self- or parent-report at four weeks were classified has having PCS. When possible, presence of PCS at a follow-up clinical visit was confirmed through review of the electronic medical record. The remaining subjects were classified as having acute concussion symptoms (ACS). Those subjects with PCS at four weeks were contacted again at eight weeks for an additional SCAT-3 phone evaluation. Seven subjects who failed to complete a follow-up SCAT-3 interview at four weeks and lacked a follow-up clinical visit were excluded from the study.
  • ACS acute concussion symptoms
  • RNA collection, processing, and quantification Saliva was collected from each subject via expectoration at the time of enrollment in a non-fasting state after an oral-tap water rinse. Each subject expectorated into an Oragene RE-100 saliva collection kit (DNA Genotek; Ottawa, Canada. Samples were shaken by hand 5-10 times and stored at room temperature for up to ten days prior to transfer into a 4°C refrigerator. RNA was extracted with a Norgen Circulating and Exosomal RNA Purification Kit (Norgen Biotek, Ontario, Canada) per manufacturer instructions as we have previously reported (J. Head Trauma Rehabil., 1993). RNA concentrations were quantified with a Nanodrop Spectrophotmeter and stored at -80°C prior to sequencing.
  • RNA yield and quality were assessed with the Agilent 2100 Bioanalyzer before library construction. Sequencing of salivary RNA occurred at the Penn State Genomics Core Facility using a NEXTflex Small RNA-Seq Kit v3 (Bioo Scientific; Austin, Texas), an Illumina HiSeq 2500 Instrument, and a targeted depth of three million reads per sample. Reads were aligned to the hg38 build of the human genome using Partek Flow software (Partek; St. Louis, Missouri) and the SHRiMP2 aligner. Total miRNA counts within each sample were quantified with miRBase microRNA v21. Three saliva samples with less than 2.5 ⁇ 10 4 total miRNA counts were excluded from the final analysis, resulting in 52 final mTBI samples.
  • Concentrations of miRNAs were utilized in the regression as ratios, providing a second level of control for variation in total miRNA across samples.
  • Accuracy was determined by measuring area under the curve (AUC) on a receiver operating characteristics plot and validated with a 100-fold Monte Carlo cross validation technique.
  • AUC for the top performing group of miRNAs was compared against the AUC for three clinical measures: 1) total symptom score on the child-response portion of the SCAT-3; 2) total symptom score on the parent-response portion of the SCAT-3; and 3) modified PCS risk score utilizing sex, age, prior concussion history, headache, fatigue, processing difficulty, and migraine history, as previously described by Zemek and colleagues (Babcock et al., 2013).
  • the top 15 miRNAs were inspected for functional relevance to brain injury and repair using DIANA mirPath v3 online software (Hyper Text Transfer Protocol Secure (HTTPS)://snf-515788.vm.okeanos.grnet.gr/).
  • DIANA mirPath v3 online software Hyper Text Transfer Protocol Secure (HTTPS)://snf-515788.vm.okeanos.grnet.gr/).
  • HTPS Hos Text Transfer Protocol Secure
  • the mean read count was 2.1 ⁇ 10 5 reads per sample and 437 miRNAs were detected in at least 22/30 samples.
  • 437 miRNAs 14 demonstrated nominal differences between ACS and PCS groups on Mann-Whitney testing (Table 4B), but none survived multiple testing corrections.
  • 3 were down-regulated in ACS subjects and 11 were up-regulated.
  • a PLSDA employing miRNA expression levels for all 437 miRNAs achieved partial spatial separation of ACS and PCS groups while accounting for 21.5 % of the variance in the dataset (Tables 29A-B).
  • the 15 miRNAs most critical for separation of ACS and PCS subjects were identified by VIP score ( Fig. 18 ).
  • Total miRNA profiles achieve partial separation of ACS and PCS groups.
  • PLSDA shows spatial separation of ACS and PCS groups using salivary miRNA profiles ( Fig. 19 ).
  • Targeted GO pathways included neurotrophin TRK signaling (34 genes), axon guidance (61 genes), and nervous system development (56 genes).
  • KEGG pathways of interest were glioma (14 genes), FOXO signaling (29 genes), and Wnt signaling (22 genes).
  • Hierarchical clustering analysis of the 15 miRNAs demonstrated three distinct clusters of miRNAs based upon gene target function: miR-629-3p and miR-133a-5p; let-7a-5p and let-7b-5p; miR-320c and miR-200b-3p ( Fig. 20 ).
  • Table 30 Fold changes and p-values between PCS and ACS groups for all interrogated miRNAs (in order of p-values).
  • the present disclosure also contemplates a kit suitable for determining whether a subject has a disease, disorder, or condition (such as a traumatic brain injury) including 2 or more miRNA probes of a probe set.
  • Each miRNA probe may include a ribonucleotide sequence corresponding to a specific miRNA described herein.
  • the kit further may include a solid support attached to the 2 or more miRNA probes.
  • the kit may further include at least one of the following: (a) one randomly-generated miRNA sequence adapted to be used as a negative control; (b) at least one oligonucleotide sequence derived from a housekeeping gene, used as a standardized control for total RNA degradation; or (c) at least one randomly-generated sequence used as a positive control.
  • Table 31 Genes involved in neurodevelopmental pathways are targeted by the 15 miRNAs of interest. Gene Targets Gene Ontology Category Neurotrophin TRK Signaling Pathway IRS2, SOS2, CAMK4, NRAS, CRKL, AGO3, PRKCI, AP2B1, SORT1, RAP1A.
  • miRNA-320c is associated with specific symptoms at 4-weeks ( Fig. 27 ).
  • salivary microRNAs exhibit a highprognostic potential, areasily measured in saliva, are altered following mTBI, are functionally related or interactive with genes expressed in the grain, predict TBI symptom duration, and are associated with the character of clinical or other physical symptoms of TBI.
  • Fig. 28 shows Regression analysis using Modified Clinical Prediction tool (Zemek et al., 2016).
  • Clinical risk score considers factors including sex, age, prior concussion with symptoms more than 7 days (headache, fatigue, processing difficulty).
  • Figs. 29A-29B present a logistic regression model using a subset of those miRNAs to predict PCS status.
  • Table 32A Fold changes and p-values for all salivary miRNAs compared across PCS and ACS groups.
  • Table 32B nominal differences between ACS and PCS groups on Mann-Whitney testing FC (in ACS) log2(FC) p.value - LOG10(p) hsa-miR-769-5p 1.82 0.86 0.002 2.69 hsa-miR-215-5p 2.38 1.25 0.024 1.62 hsa-mir-769 2.47 1.30 0.025 1.60 hsa-mir-320c-1 0.44 -1.18 0.028 1.55 hsa-mir-194-2 1.42 0.51 0.028 1.55 hsa-mir-199a-1 2.78 1.47 0.032 1.49 hsa-mir-4792 1.83 0.87 0.033 1.48 hsa-miR-140-3p 1.84 0.88 0.036 1.45 hsa-miR-629-5p 0.66 -0.59 0.036 1.44 h
  • Fig. 31 shows comparative (an under-performing) logistic regression model using child SCAT-3 scores.
  • MiRNAs that are useful for detection and prediction of PCS miR-769, miR-769-3p, miR-769-5p, miR-320c-1, miR-320c-1-3p, miR-320c-1-5p, miR-4792, miR-4792-3p, miR-4792-5p, miR-140, miR-140-3p, miR-140-5p, miR-629, miR-629-3p, miR-629-5p, miR-192, miR-192-3p, miR-192-5p, miR-145, miR-145-3p, miR-145-5p, let-7a, let-7a-3p, let-7s-5p, miR-133a, miR-133a-3p, miR-133a-5p, miR-1307, miR-1307-3p, miR-1307-5p, miR-200b, miR-200b-3p, miR-200b-5p, let-7a, let-7a-3p, let-7a-5p, miR-450
  • Salivary microRNA was collected from 50 children (ages 7-21) presenting to a tertiary care center with a physician-diagnosed mild traumatic brain injury at acute (0-3 days after injury), sub-acute (7-17 days after injury), and chronic ( ⁇ 28 days after injury) time-points. Injury mechanism and demographic features were recorded. Subjective symptoms were assessed with SCAT-5 survey, and functional symptoms of balance and cognition (e.g. processing speed, divided attention performance) were measured with the ClearEdge ⁇ Concussion Toolkit. Saliva microRNA levels were quantified with high throughput RNA sequencing. Spearman's rank correlations were used to identify potential relationships between microRNA levels and four continuous variables: 1) days since injury; 2) ClearEdge TM balance score; 3) ClearEdge TM cognitive score; and 4) participant age.
  • Salivary miRNAs that exhibit circadian rhythms in their expression and abundance
  • Saliva collection at intervals over a day. Eleven human subject volunteers participated in the study and provided saliva samples at various times of day on repeated days in three different rounds of sample collection. Saliva was collected via a swab and prepared using a salivary preparation kit.
  • NGS next generation sequencing
  • SUNYMAC SUNY Molecular Analysis Core
  • TruSeq ® Small RNA Library Preparation Kit protocol Illumina, San Diego, CA
  • Alignment of the NGS reads was performed to the miRbase21 database using the SHRRiMP2 ® algorithm in Partek Flow software to identify mature miRNAs.
  • Mapping of microbiome reads was performed using Kraken software and OneCodex ® software to identify only microbes that were consistently found in both.
  • reads or “read-counts” should be understood to apply to any method for adjusting miRNA or microbiome expression data to account for variations between samples, such as using the expression levels of certain control miRNAs or metabolites that are always present at a predictable level in saliva to normalize the levels of all miRNAs in the samples so they can be compared more accurately.
  • fluorescence methods are used to determine miRNA and/or microbiome levels.
  • separate groups of ligands targeting some or all of the target miRNA described herein are anchored in groups on a substrate.
  • the target miRNA and microbiome sequences are tagged with a fluorescent tag (or non-fluorescent dye) either before or after it binds to the ligand.
  • a relative intensity at each ligand group may be a measure of quantity of miRNA and/or microbiome present.
  • This method may be implemented on a chip-type assay. Other suitable chip-type-assays may be used to determine miRNA and/or microbiome levels.
  • a two-way analysis of variance was performed in the Collection 1 and 2 sample sets to identify miRNAs and microbes that varied significantly according to collection time but not the day of collection (which could have been strongly affected by daily variation in routines). A subset of these miRNAs and microbes were then used in a third sample set to assess the accuracy of prediction for the time of collection using multivariate linear regression.
  • MiRNAs that showed the strongest circadian oscillations were termed circaMiRs and examined for being predicted regulators of a total of 139 annotated circadian genes using Ingenuity Pathway Analysis (IPA) software. CircaMiRs targeting circadian genes were then examined for evidence of association with the strongest circadian-oscillating microbes using Pearson correlation analysis. The functions of the genes targeted by circaMiRs were then examined for their specific biological functions using IPA and miRpath software.
  • Table 33 Accuracy of 19 circaMiRs to predict collection time. Multiple R P value Margin of Error Collection 1 0.990 0.003929 12.9% Collection 2 0.878 0.000031 18.1% Collection 3 0.875 0.000040 26.0% (no 4 am) 0.938 2.28e -10 15.7%
  • Group A and Group B circa MiRs are described in Table 34.
  • Table 34 Groups A and B circaMiRNAs Group A circaMiRs Group B circaMiRs 1 hsa-miR-106b-3p hsa-let-7a-5p 2 hsa-miR-128-3p hsa-let-7d-3p 3 hsa-miR-130a-3p hsa-miR-101-3p 4 hsa-miR-15a-5p hsa-miR-10b-5p 5 hsa-miR-192-5p hsa-miR-125b-2-3p 6 hsa-miR-199a-3p hsa-miR-1307-5p 7 hsa-miR-199b-3p hsa-miR-140-3p 8 hsa-miR-203a-3p hsa-miR-142-3p 9 hsa-miR
  • Tables 34 lists circaMiRs that may be used to distinguish healthy subjects from subjects having a disease or disorder using the methods described herein or which may be normalized to adjust for circadian fluctuations in concentration or abundance.
  • Other miRNAs sharing the same seed sequences as any of the miRNAs in the above tables may be used for these purposes.
  • a heat map clustering of expression data for the 19 miRNAs changed according to collection time in 24 samples from 4 subjects across 3 days of sampling (days 1, 3, 7) at a frequency of 2 times/day (8 am, 8 pm) is shown in Fig. 33 .
  • a heat map clustering of expression data for the 19 miRNAs changed according to collection time in 48 samples from 3 subjects across 4 days of sampling (days 1, 5, 10, 15) at a frequency of 4 times/day (8 am, 12 pm, 4 pm, 8 pm) is shown in Fig. 34 .
  • Normalized data for 1 of the top 19 miRNAs shown for 3 of the subjects in Collection 3 is shown in Fig. 35 .
  • Diagnostic and prognostic methods using miRNAs that correlate or associate with particular conditions, disorders or diseases, such as TBI or concussive injuries and that also exhibit temporal or circadian fluctuations may be normalized based on known circadian fluctuations in the circa-MiRs. Alternatively, diagnostic and prognostic methods may control for these circadian fluctuations by obtaining samples at a fixed time of day so as to avoid the fluctuations. In other embodiments, a diagnostic or prognostic method may use miRNAs that are exhibit constant or relatively invariant expression so as to avoid noise or error introduced by circadian or other temporal fluctuations in miRNA abundance or concentration.
  • Links are disabled by deletion of http: or by insertion of a space or underlined space before www.
  • a numeric value may have a value that is +/- 0.1% of the stated value (or range of values), +/- 1% of the stated value (or range of values), +/- 2% of the stated value (or range of values), +/- 5% of the stated value (or range of values), +/- 10% of the stated value (or range of values), +/- 15% of the stated value (or range of values), +/-20% of the stated value (or range of values), etc. Any numerical range recited herein is intended to include all sub-ranges subsumed therein.
  • the words "preferred” and “preferably” refer to embodiments of the technology that afford certain benefits, under certain circumstances. However, other embodiments may also be preferred, under the same or other circumstances. Furthermore, the recitation of one or more preferred embodiments does not imply that other embodiments are not useful, and is not intended to exclude other embodiments from the scope of the technology.
  • compositional percentages are by weight of the total composition, unless otherwise specified.
  • the word "include,” and its variants is intended to be non-limiting, such that recitation of items in a list is not to the exclusion of other like items that may also be useful in the materials, compositions, devices, and methods of this technology.
  • the terms “can” and “may” and their variants are intended to be non-limiting, such that recitation that an embodiment can or may comprise certain elements or features does not exclude other embodiments of the present invention that do not contain those elements or features.
  • first and second may be used herein to describe various features/elements (including steps), these features/elements should not be limited by these terms, unless the context indicates otherwise. These terms may be used to distinguish one feature/element from another feature/element. Thus, a first feature/element discussed below could be termed a second feature/element, and similarly, a second feature/element discussed below could be termed a first feature/element without departing from the teachings of the present invention.
  • references herein does not constitute an admission that those references are prior art or have any relevance to the patentability of the technology disclosed herein. Any discussion of the content of references cited is intended merely to provide a general summary of assertions made by the authors of the references, and does not constitute an admission as to the accuracy of the content of such references.

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Organic Chemistry (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Engineering & Computer Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Molecular Biology (AREA)
  • Zoology (AREA)
  • Genetics & Genomics (AREA)
  • Pathology (AREA)
  • Biophysics (AREA)
  • Analytical Chemistry (AREA)
  • Wood Science & Technology (AREA)
  • Neurology (AREA)
  • Physics & Mathematics (AREA)
  • Biochemistry (AREA)
  • Immunology (AREA)
  • Microbiology (AREA)
  • Surgery (AREA)
  • Veterinary Medicine (AREA)
  • Public Health (AREA)
  • General Engineering & Computer Science (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Medical Informatics (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Animal Behavior & Ethology (AREA)
  • Biotechnology (AREA)
  • Neurosurgery (AREA)
  • Physiology (AREA)
  • Psychology (AREA)
  • Hematology (AREA)
  • Medicinal Chemistry (AREA)
  • Cell Biology (AREA)
  • Pulmonology (AREA)
  • Toxicology (AREA)
  • Gastroenterology & Hepatology (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
  • Investigating Or Analysing Biological Materials (AREA)
EP18771563.6A 2017-03-23 2018-03-23 Analysis and prediction of traumatic brain injury and concusion symptoms Active EP3600472B1 (en)

Applications Claiming Priority (5)

Application Number Priority Date Filing Date Title
US201762475698P 2017-03-23 2017-03-23
US201762480079P 2017-03-31 2017-03-31
US201762502107P 2017-05-05 2017-05-05
US201862623145P 2018-01-29 2018-01-29
PCT/US2018/024111 WO2018175941A1 (en) 2017-03-23 2018-03-23 Analysis and prediction of traumatic brain injury and concusion symptoms

Publications (3)

Publication Number Publication Date
EP3600472A1 EP3600472A1 (en) 2020-02-05
EP3600472A4 EP3600472A4 (en) 2020-12-30
EP3600472B1 true EP3600472B1 (en) 2024-04-17

Family

ID=63584789

Family Applications (1)

Application Number Title Priority Date Filing Date
EP18771563.6A Active EP3600472B1 (en) 2017-03-23 2018-03-23 Analysis and prediction of traumatic brain injury and concusion symptoms

Country Status (7)

Country Link
US (1) US11453914B2 (ko)
EP (1) EP3600472B1 (ko)
JP (1) JP2020512017A (ko)
KR (1) KR102621064B1 (ko)
AU (1) AU2018240473B2 (ko)
CA (1) CA3057324A1 (ko)
WO (1) WO2018175941A1 (ko)

Families Citing this family (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB201603967D0 (en) 2016-03-08 2016-04-20 Univ Birmingham Biomarkers of traumatic brain injury
WO2019165267A1 (en) * 2018-02-22 2019-08-29 The Regents Of The University Of California Methods for treating brain injury
US11529054B2 (en) * 2018-07-25 2022-12-20 The Charles Stark Draper Laboratory, Inc. Method and system for post-traumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI) diagnosis using magnetic resonance spectroscopy
CN109266739A (zh) * 2018-11-29 2019-01-25 成都仕康美生物科技有限公司 一种检测脑损伤的miRNA标志物、试剂盒、应用
CR20210466A (es) * 2019-02-14 2022-02-08 Marker Diagnostics Uk Ltd Biomarcadores salivales de lesión cerebral
CN109825597B (zh) * 2019-04-19 2021-11-26 中国医学科学院肿瘤医院 食管癌前病变miRNAs标志物组、应用与诊断系统
WO2021132725A1 (ja) * 2019-12-27 2021-07-01 国立大学法人弘前大学 認知機能障害のバイオマーカー及びその検出薬、被験者の認知機能障害を検査する方法、認知機能障害の治療又は改善手段を被験者に提示する方法、並びに、認知機能障害の治療又は改善物質のスクリーニング方法
US12091716B2 (en) 2020-01-15 2024-09-17 Mayo Foundation For Medical Education And Research Methods and materials for identifying and treating traumatic brain injury
US20240124931A1 (en) * 2022-10-15 2024-04-18 Renato Rozental Material and method for diagnosis of traumatic brain injury

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9605315B2 (en) * 2014-03-26 2017-03-28 The University Of Montana Detection of traumatic brain injury
EP3247798A4 (en) 2015-01-21 2019-01-02 The Research Foundation for the State University of New York Identification of epigenetic biomarkers in the saliva of children with autism spectrum disorder
EP3347493B1 (en) * 2015-09-08 2022-03-30 The Translational Genomics Research Institute Biomarkers and methods of diagnosing mild traumatic brain injuries
KR102065863B1 (ko) 2015-09-11 2020-01-13 아처 다니엘 미드랜드 캄파니 이소이다이드의 제조 방법
GB201603967D0 (en) 2016-03-08 2016-04-20 Univ Birmingham Biomarkers of traumatic brain injury

Also Published As

Publication number Publication date
EP3600472A4 (en) 2020-12-30
US20200277676A1 (en) 2020-09-03
AU2018240473B2 (en) 2023-12-14
JP2020512017A (ja) 2020-04-23
EP3600472A1 (en) 2020-02-05
AU2018240473A1 (en) 2019-10-03
CA3057324A1 (en) 2018-09-27
KR20200024127A (ko) 2020-03-06
KR102621064B1 (ko) 2024-01-03
WO2018175941A1 (en) 2018-09-27
US11453914B2 (en) 2022-09-27

Similar Documents

Publication Publication Date Title
EP3600472B1 (en) Analysis and prediction of traumatic brain injury and concusion symptoms
Di Pietro et al. MicroRNAs as novel biomarkers for the diagnosis and prognosis of mild and severe traumatic brain injury
Di Pietro et al. Salivary MicroRNAs: diagnostic markers of mild traumatic brain injury in contact-sport
Hara et al. Serum microRNA miR-501-3p as a potential biomarker related to the progression of Alzheimer’s disease
Ricci et al. MicroRNAs as biomarkers in amyotrophic lateral sclerosis
KR102359013B1 (ko) 자폐 스펙트럼 장애의 분석
Kumar et al. Circulating miRNA biomarkers for Alzheimer's disease
CN105861712B (zh) 使用来自体液的miRNA来早期检测和监控轻度认知障碍(MCI)和阿尔茨海默病(AD)的方法
Eisenberg et al. Distinctive patterns of microRNA expression in primary muscular disorders
CN113286895A (zh) 用于诊断和治疗脑疾患，尤其是认知障碍的长的非编码RNA(lncRNA)
Santpere et al. Transcriptional network analysis in frontal cortex in L ewy body diseases with focus on dementia with L ewy bodies
Enright et al. Discovery and validation of blood micro RNA s as molecular biomarkers of epilepsy: Ways to close current knowledge gaps
Tarallo et al. microRNAs as biomarkers in Pompe disease
KR20140044375A (ko) 알츠하이머병을 나타내는 마이크로rna 바이오마커들
US20200157626A1 (en) Method for diagnosing or monitoring conditions characterized by abnormal temporal variations and method of normalizing epigenetic data to compensate for temporal variations
Zadehbagheri et al. Profiling of miRNAs in serum of children with attention-deficit hyperactivity disorder shows significant alterations
Wang et al. MicroRNA-134 plasma levels before and after treatment with valproic acid for epilepsy patients
Salloum-Asfar et al. Circulating non-coding RNAs as a signature of autism spectrum disorder symptomatology
Magen et al. Muscle microRNAs in the cerebrospinal fluid predict clinical response to nusinersen therapy in type II and type III spinal muscular atrophy patients
Ye et al. Gene co-expression network for analysis of plasma exosomal miRNAs in the elderly as markers of aging and cognitive decline
Minutti-Zanella et al. miRNAs in multiple sclerosis: A clinical approach
Popov et al. Micro RNA HSA-486-3P gene expression profiling in the whole blood of patients with autism
Mengel-From et al. Circulating microRNAs disclose biology of normal cognitive function in healthy elderly people–a discovery twin study
Levitskiy et al. Longitudinal stability of salivary microRNA biomarkers in children and adolescents with autism spectrum disorder
CN105132525B (zh) miRNA分子在精神分裂症的诊断和预后中的用途

Legal Events

Date Code Title Description
STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE INTERNATIONAL PUBLICATION HAS BEEN MADE

PUAI Public reference made under article 153(3) epc to a published international application that has entered the european phase

Free format text: ORIGINAL CODE: 0009012

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: REQUEST FOR EXAMINATION WAS MADE

17P Request for examination filed

Effective date: 20190923

AK Designated contracting states

Kind code of ref document: A1

Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR

AX Request for extension of the european patent

Extension state: BA ME

DAV Request for validation of the european patent (deleted)
DAX Request for extension of the european patent (deleted)
A4 Supplementary search report drawn up and despatched

Effective date: 20201126

RIC1 Information provided on ipc code assigned before grant

Ipc: C07H 21/02 20060101ALI20201120BHEP

Ipc: A61M 1/00 20060101AFI20201120BHEP

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: EXAMINATION IS IN PROGRESS

17Q First examination report despatched

Effective date: 20220531

REG Reference to a national code

Ref country code: DE

Ref legal event code: R079

Ref document number: 602018068217

Country of ref document: DE

Free format text: PREVIOUS MAIN CLASS: A61M0001000000

Ipc: C12Q0001688300

Ref country code: DE

Free format text: PREVIOUS MAIN CLASS: A61M0001000000

Ipc: C12Q0001688300

GRAP Despatch of communication of intention to grant a patent

Free format text: ORIGINAL CODE: EPIDOSNIGR1

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: GRANT OF PATENT IS INTENDED

RIC1 Information provided on ipc code assigned before grant

Ipc: C12Q 1/6883 20180101AFI20231030BHEP

INTG Intention to grant announced

Effective date: 20231117

GRAS Grant fee paid

Free format text: ORIGINAL CODE: EPIDOSNIGR3

GRAA (expected) grant

Free format text: ORIGINAL CODE: 0009210

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE PATENT HAS BEEN GRANTED

AK Designated contracting states

Kind code of ref document: B1

Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR

REG Reference to a national code

Ref country code: GB

Ref legal event code: FG4D

REG Reference to a national code

Ref country code: CH

Ref legal event code: EP

REG Reference to a national code

Ref country code: IE

Ref legal event code: FG4D

Ref country code: DE

Ref legal event code: R096

Ref document number: 602018068217

Country of ref document: DE

REG Reference to a national code

Ref country code: LT

Ref legal event code: MG9D

REG Reference to a national code

Ref country code: NL

Ref legal event code: MP

Effective date: 20240417

REG Reference to a national code

Ref country code: AT

Ref legal event code: MK05

Ref document number: 1677297

Country of ref document: AT

Kind code of ref document: T

Effective date: 20240417

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: NL

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20240417

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: NL

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20240417

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: IS

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20240817

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: BG

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20240417

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: FI

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20240417

Ref country code: HR

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20240417

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: GR

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20240718

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: PT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20240819